区域广告展示赋能商家曝光数据集

核心在于对广告曝光日志进行区域化聚合与赋能效果关联。规则可简述为：数据基础：采集每次广告展示的核心数据，包括：广告ID、商家ID、用户所在/目标区域、时间戳、广告位、展示渠道等。区域聚合：将海量的单次展示数据，按时间粒度（如天/周）、区域粒度（如商圈、行政区）、商家/行业维度进行聚合，计算总曝光量、覆盖用户数等指标。“赋能”关联：将聚合后的广告曝光数据与商家的后端经营数据（如页面浏览量、券领取量、核销量、GMV）进行关联分析，计算“曝光-转化”效率指标（如每千次曝光带来的订单量）。算法应用：可能使用归因模型（如最后一次触点归因）来合理分配转化功劳给不同的广告曝光。

The core of this dataset focuses on regional aggregation of advertisement impression logs and correlation with advertising empowerment effects. The relevant rules can be briefly summarized as follows:
1. Data basis: Core data for each advertisement impression is collected, including ad ID, merchant ID, user's location/target region, timestamp, ad slot, display channel, and other relevant metrics.
2. Regional aggregation: Massive individual advertisement impression data is aggregated across time granularities (e.g., daily, weekly), regional granularities (e.g., business district, administrative district), and merchant/industry dimensions, with indicators such as total ad impressions and number of unique users reached calculated.
3. "Empowerment" association: Correlation analysis is performed between the aggregated advertisement impression data and merchants' backend operational data (e.g., page views, coupon claims, coupon redemptions, Gross Merchandise Volume (GMV)), and "exposure-to-conversion" efficiency metrics (e.g., order volume per thousand ad impressions) are derived.
4. Algorithm application: Attribution models (e.g., last-click attribution) may be employed to reasonably allocate conversion credits to distinct advertisement impressions.

搜集汇总

背景与挑战

背景概述

该数据集由贵州品得科技有限责任公司自行产生，规模为3.67GB，每日更新，主要用于区域化精准广告投放优化和商家曝光效果评估。其特点包括通过区域聚合和归因算法分析广告曝光与商家经营数据的关联，支持广告策略优化、市场潜力评估和竞品分析等应用场景。